In its report ESMA provides valuable insights into the opportunities and challenges presented by the increasing use of AI in the securities markets. It also highlights the need for a balanced and proactive approach as to the regulation of AI in order to ensure that it is used in a safe and effective manner that promotes market integrity and investor protection. Human oversight remains key.

ESMA notes that AI could transform the securities markets by improving efficiency, increasing accuracy, and reducing costs. However, it also highlights several risks and challenges that must be addressed to ensure the safe and effective use of AI in the securities markets. 


Risk management 

AI can assist financial organizations in managing risk more successfully. It can evaluate data to find potential dangers and offer mitigation techniques. Financial institutions can benefit from this to lower the risk of losses and enhance their overall financial performance. 

Fraud identification  

Artificial intelligence can be used to spot securities market fraud. Machine learning algorithms are able to evaluate enormous amounts of data, spot trends, and spot abnormalities that can point to dishonest activity. The ESMA has already started projects in this field after realizing the potential of AI in fraud detection.  


AI can aid in the improvement of investing choices. To find trends and patterns, it may evaluate a lot of data from several sources, like financial accounts, news articles, and social media. Investors may be able to lower the risk of losses and make better judgments as a result. 

Trading strategies 

Trading strategies can be improved by AI, and trades can be carried out more quickly. It has the ability to instantly assess market data and forecast upcoming trends. This can enhance trading performance and enable traders to make quicker, more precise judgments.  

Key risks and challenges

Biased data and discrimination 

One of the key risks is the potential for AI to amplify existing biases and discrimination. AI systems are only as good as the data they are trained on and the biased date can result in biased outcomes. This would have significant implications for market integrity and investor protection.  

Supervision and monitoring 

Another risk is that AI could increase the speed and complexity of trading, making it more difficult for regulators to monitor and supervise. AI systems can execute trades at much higher speeds than humans and can quickly adapt to changing market conditions. This could potentially make it more difficult for regulators to detect and respond to market abuse and manipulation. 

Measures proposed by ESMA to reduce risks 

To address the risks, including those above mentioned, ESMA’s report recommends a number of measures. These include improving the quality and transparency of data used to train AI systems, developing robust oversight and governance framework for the use of AI in the securities markets, and enhancing the ability of regulators to monitor and supervise the use of AI.  Maintaining effective human oversight and upskilling management are considered key. In this context, it is important to ascertain whether existing governance arrangements and compliance departments are fit for purpose.